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GreenDroid: Automated Diagnosis of Energy Inefficiency for Smartphone Applications
PrePrint
ISSN: 0098-5589
Smartphone applications’ energy efficiency is vital, but many Android applications suffer from serious energy ineffi-ciency problems. Locating these problems is labor-intensive and automated diagnosis is highly desirable. However, a key chal-lenge is the lack of a decidable criterion that facilitates automated judgment of such energy problems. Our work aims to address this challenge. We conducted an in-depth study of 173 open-source and 229 commercial Android applications, and observed two common causes of energy problems: missing deactivation of sensors or wake locks, and cost-ineffective use of sensory da-ta. With these findings, we propose an automated approach to diagnosing energy problems in Android applications. Our ap-proach explores an application’s state space by systematically executing the application using Java PathFinder (JPF). It moni-tors sensor and wake lock operations to detect missing deactivation of sensors and wake locks. It also tracks the transformation and usage of sensory data and judges whether they are effectively utilized by the application using our state-sensitive data utili-zation metric. In this way, our approach can generate detailed reports with actionable information to assist developers in validat-ing detected energy problems. We built our approach as a tool, GreenDroid, on top of JPF. Technically, we addressed the chal-lenges of generating user interaction events and scheduling event handlers in extending JPF for analyzing Android applications. We evaluated GreenDroid using 13 real-world popular Android applications. GreenDroid completed energy efficiency diagnosis for these applications in a few minutes. It successfully located real energy problems in these applications, and additionally found new unreported energy problems that were later confirmed by developers.
Citation:
Yepang Liu, S.C. Cheung, Jian Lu, Chang Xu, "GreenDroid: Automated Diagnosis of Energy Inefficiency for Smartphone Applications," IEEE Transactions on Software Engineering, 23 May 2014. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TSE.2014.2323982>
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